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ORCID5th NILM@SenSys 2020: Virtual Event, Japan
- NILM '20, Proceedings of the 5th International Workshop on Non-Intrusive Load Monitoring, November18, 2020, Virtual Event, Japan. ACM 2020, ISBN 978-1-4503-8191-8
- Benjamin Völker
, Marc Pfeifer, Philipp M. Scholl, Bernd Becker:
Annoticity: A Smart Annotation Tool and Data Browser for Electricity Datasets. 1-5 - Xinlei Chen, Omid Ardakanian:
Solar Disaggregation: State of the Art and Open Challenges. 6-10 - Jack Barber, Heriberto Cuayáhuitl, Mingjun Zhong, Wenpeng Luan:
Lightweight Non-Intrusive Load Monitoring Employing Pruned Sequence-to-Point Learning. 11-15 - Akhilesh Yadav, Anuj Sinha, Abdessamad Saidi, Christoph Trinkl, Wilfried Zörner:
NILM based Energy Disaggregation Algorithm for Dairy Farms. 16-19 - Simon Henriet, Benoit Fuentes, Umut Simsekli, Gaël Richard:
Matrix Factorization for High Frequency Non Intrusive Load Monitoring: Definitions and Algorithms. 20-24 - François Culière, Laetitia Leduc, Alexander Belikov:
Bayesian model of electrical heating disaggregation. 25-29 - Rubén Nieto, Laura de Diego-Otón, Álvaro Hernández, Jesús Ureña:
Finite Precision Analysis for an FPGA-based NILM Event-Detector. 30-33 - Mohammad Khazaei, Lina Stankovic, Vladimir Stankovic:
Evaluation of low-complexity supervised and unsupervised NILM methods and pre-processing for detection of multistate white goods. 34-38 - Richard Jones, Christoph Klemenjak, Stephen Makonin, Ivan V. Bajic:
Stop: Exploring Bayesian Surprise to Better Train NILM. 39-43 - Shamim Ahmed, Marc Bons:
Edge computed NILM: a phone-based implementation using MobileNet compressed by Tensorflow Lite. 44-48 - Darwish Darwazeh, Jean Duquette, Burak Gunay:
Virtual metering of heat supplied by hydronic perimeter heaters in variable air volume zones. 49-53 - Christy Green, Srinivas Garimella:
Non-Intrusive Load Monitoring of Water Heaters Using Low-Resolution Data. 54-58 - Abhinav Srivastava, Paras Tehria, Basant K. Pandey:
Energy Disaggregation for Small and Medium Businesses and their Operational Characteristics. 59-63 - David Murray, Lina Stankovic, Vladimir Stankovic:
Explainable NILM Networks. 64-69 - João Gois, Christoph Klemenjak, Lucas Pereira:
On the Relationship between Seasons of the Year and Disaggregation Performance. 70-74 - Andreas Reinhardt, Mazen Bouchur:
On the Impact of the Sequence Length on Sequence-to-Sequence and Sequence-to-Point Learning for NILM. 75-78 - R. Gopinath, Mukesh Kumar, K. J. Lokesh, Kota Srinivas:
Performance Analysis of Similar Appliances Identification using NILM Technique under Different Data Sampling Rates. 79-83 - Anthony Faustine, Lucas Pereira, Hafsa Bousbiat, Shridhar Kulkarni:
UNet-NILM: A Deep Neural Network for Multi-tasks Appliances State Detection and Power Estimation in NILM. 84-88 - Zhenrui Yue, Camilo Requena Witzig, Daniel Jorde, Hans-Arno Jacobsen:
BERT4NILM: A Bidirectional Transformer Model for Non-Intrusive Load Monitoring. 89-93 - Faisal M. Almutairi, Aritra Konar, Ahmed S. Zamzam, Nicholas D. Sidiropoulos:
Phased: Phase-Aware Submodularity-Based Energy Disaggregation. 94-98 - Rithwik Kukunuri, Nipun Batra, Hongning Wang:
An Open Problem: Energy Data Super-Resolution. 99-102
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